Identifying environmentally important supply chain clusters in the automobile industry

Shigemi Kagawa, Sangwon Suh, Yasushi Kondo, Keisuke Nansai

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

In this paper, we develop a new approach that combines the spectral clustering method and input-output analysis to detect environmentally important supply chain clusters. The newly developed method was applied to automobile manufacturing in Japan, and major clusters with high energy intensities in the automobile supply chain were identified. This paper proposes that the car manufacturers will be able to regularly publish their life-cycle assessment reports with a focus on the indirect energy consumptions within the critical supply chains and request key auto-part manufacturers in the cluster to reduce the indirect consumptions through the relevant supply chain engagement.

Original languageEnglish
Pages (from-to)265-286
Number of pages22
JournalEconomic Systems Research
Volume25
Issue number3
DOIs
Publication statusPublished - 2013 Sep 1

Keywords

  • Energy clusters
  • Laplacian matrix
  • Spectral clustering analysis
  • Supply chain

ASJC Scopus subject areas

  • Economics and Econometrics

Fingerprint Dive into the research topics of 'Identifying environmentally important supply chain clusters in the automobile industry'. Together they form a unique fingerprint.

  • Cite this